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What’s All the Talk About AI and RPA

Robotic Process AutomationTrendsMachine Learning
Sanna Kaarlejärvi

Organizations of all types and sizes are turning to technology to automate financial management and other information-intensive work. Today we are able to automate tasks that we couldn’t even imagine doing just a decade ago. And, while finance departments have often been one of the last to automate, lately they have been making strides in this area, adopting new technologies such as robotic process automation (RPA) and artificial intelligence (AI).

Financial management, with its rules-based processes, is ideally suited for these new, innovative technologies. The demand for better, more accurate service at lower cost, and invoice visibility for real-time financial and operational reporting is driving finance departments to turn to AI and other types of automation, such as AP automation.

But what do RPA and AI really mean, in practice, for finance departments? How should we deal with these new technologies? In this blog, I will take a closer look at the topic through six key areas.

1. Robotic Process Automation is Here to Stay

RPA, which has become a generally accepted automation tool, is being used to process invoices, handle reconciliations, input data into systems, and perform other routine financial management tasks. This technology has become popular by delivering key efficiencies and cost savings. At the same time, the market has matured; software prices are low, there is plenty of RPA expertise, and user experiences with the technology have been positive. Given all of this, we predict that within the next decade a vast majority of medium and large-sized businesses will be using RPA in one way or another.

But will artificial intelligence eventually replace these “unintelligent” software robots? The answer is no. Both RPA and AI have their own roles in an organization and they complement one another. Software robots work tirelessly, using structured, digital data to handle the routine tasks they have been trained to do. AI uses different types of data to create rules, categorize and train the data to be used by RPA automation and modifies data into formats that RPA and other business software can understand.

Conversely, RPA supports AI by helping to collect the volumes of data that this intelligent technology needs to develop patterns and rules.

2. Interaction with Machines is Changing

New user interfaces, which incorporate AI, are changing the way in which we communicate with machines. As consumers we’ve become accustomed to using speech to control our mobile applications, and as business users we are beginning to demand similar capabilities and usability from business software.

For example, with the help of digital assistants and chatbots, business users can interact with software in a more human, interactive way. Instead of having to manually log in to a system and create queries to figure out a customer’s payment issue, the user can get the same information from a digital assistant via speech.

Self-service applications that are available anywhere, anytime are becoming more pervasive and we can expect this trend to continue. We predict that most routine requests for financial management information will handled by a chatbot in the future. As response times to requests become faster, finance professionals will be able to turn their focus to tasks that require their specific expertise and experience.

3. Digitalization Automates Internal Processes

Organizations must renew and automate their internal processes in order to support digitalization initiatives. Real-time transactions, from an Uber ride, a purchase at an Amazon cashier-less convenience store or a deposit or withdrawal at a bank, for example, are also available in real time for use by Finance to make payments, recognize revenue or manage account balances . This real-time exchange of data is critical for automating internal processes and reporting.

At the same time, as business becomes more and more digital, Finance can no longer afford to maintain outdated procedures. It’s unacceptable these days, for example, for the report of the previous month’s revenue to just become available halfway through the next month. To address this, the Finance department needs to become closely involved in refining current business processes as well as developing new ones so that it can support and benefit from digitalization .

4. Data is the New Currency

In addition to helping businesses guide their actions based on knowledge, data helps them automate processes. Those companies that can leverage their data to optimize operations or create new lines of business will succeed. But firms need to be wary of broken, incomplete or inaccurate data which can lead to broken processes and inaccurate information.

Any problems with data often become apparent when you use it for automation and reporting. It’s important to pay attention to data collection in order to improve your data. Different data types must have owners who are responsible for the quality of that data and the processes used to maintain it.

5. Don’t Lock Yourself to One Technology

No single technology will provide all the answers. The goal of adopting any new technology should be to support a broader business goal, such as improving reporting, increasing automation and smoother processes or providing better usability. As a general rule, investments should be made in automation and intelligence – not in any single technology. The reason for this is that new technologies come and go, and in an evolving market, it is difficult to guess which technology will be on top in five years.

6. Experiment Continuously

When it comes to implementing new and innovative technologies, different rules apply than with established technologies. You cannot rely on a lessons-learned session one year after the project was started. Instead, you should experiment with different technologies and services incrementally and through small investments. The advent of cloud computing allows us to do just that, and it is also driving prices down. For example, you can find numerous free tools online to experiment with AI, and the only cost you have is the time you spend working on it.

Development happens iteratively, in short cycles. Using a new technology requires us to learn by doing, sharing information and cooperating across organizational boundaries. Crowdsourcing allows us to tap into the know-how of a global pool of expertise in order to solve our problems cost-efficiently. Development is a continuous process, and at the same time it helps organizations and operations evolve.

New technologies enable us to achieve great things: better productivity, easier ways to work, less numbing routines, increased information and a better user experience. The way to accomplish these goals is to aim high, keep an open mind and have the courage to experiment with new things. I hope that you are as excited about the future as I am!

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About the Author
Sanna Kaarlejärvi
, Dooap’s CFO and leading process consultant.  In her spare time Sanna likes to exercise, especially doing cross-fit. She is also a frequent traveler.

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